interpolate values where values exist above and below. The QC test was performed on the interpolated values. If an interpolated value was > max, then the interpolated value was replaced by the max value and if an interpolated value was < min, then the interpolated value was replaced by the min value
last value when values only exist above it the QC test was performed on the extrapolated values
first non default value for the extrapolation at the surface.
For all the extrapolated values, the minimum value of the QC envelope was taken, if the QC test did not succeed.
Access to the resulting climatology
The averaged climatology can be accessed from the web site (www.ifremer.fr/medar/quality.htm)
The 4 files (annual, seasonal) are organised by vertical profiles in an auto descriptive ASCII format.
Example: Mediterranean seasonal MEDATLAS climatology (release 1) per 1 degree square (0-800m)
An additional test is the Redfield ratio : the ratio of the oxygen, nitrate and alkalinity (carbonates) concentration over the phosphate concentration has been estimated respectively to 172, 16 and 122 by Takahashi & al. (13) in the Atlantic and Indian Ocean. New studies are made in the frame of MEDAR and CYCLOPS and these values will be adjusted for the Mediterranean in a near future.
These estimate allow a visual check on the corresponding nutrients, by checking the dispersion around the reference curve.
The observed parameters were interpolated to the same standard levels as used in the climatological statistics .
Only data points with no outlier at all (Q flag=1) are used in the interpolation calculation.
Method and algorithms
The Reiniger & Ross (1968, here below referred as RR (11)) weighted parabolic interpolation is recommended by IOC and ICES and is widely used in the scientific community, in particular by Levitus at the WDC-A. The value of the correction made on the linear interpolation is a function of the difference between the linearly interpolated value and the two values extrapolated from the above and below levels.
The computation requires a profile of at least 4 levels. The authors extend the method for only 3 data points for the top and bottom of the profile, but the method is then not safe. In this case linear interpolation.was used.
In the case of no observed values between the standard level and the consecutive levels below and above, no interpolation is made.
The RR linear reference function and the weights of the parabolic function depend on variable exponents. We took the same exponent values as RR, but these values may be adjusted later.
All the interpolated parameters are initialised with the default value at the standard levels.
For MEDATLAS 1997, the following 28 vertical levels have been processed:
0, 5, 10, 20, 30, 40, 50, 60, 80, 100, 120, 160, 200, 250, 300, 400, 500, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000, 2500, 3000, et 4000 m
RR parabolic interpolation
The interpolated value of y (temperature or salinity) is a weighted mean of the two parabolic interpolations that use respectively the 3 superior data points and the 3 inferior data points.
The weights are a function of the difference between the parabolic interpolation and a reference function. This reference function is a combination of the linear interpolation and extrapolations using the 4 data points.
When none of the interpolating conditions are found, the parameter keeps the default values.
No control is made on the flags, only on the default values.
Conditions for computation
a(1) < a(2) < x < a(3) < a(4)
First a check is made that the layers above and below are not both empty:
if a(2) < x(n-1) and a(3) > x(n+1) then ys(n) = default value
ys(1) = fist observed parameter if the first observed level a(1) < xs(2)
else ys(1)=default value
Next standard level when there is only one observed level above
If there exists at least one point below the level, then the standard level is computed by using linear interpolation:
ys=flin(xs,a(1),a(2),b(1),b(2)) and flag=5 unless the standard level is an observed level
a(1), b(1) being the observed data point above the standard level and (a(2), b(2)) the observed data point below.